@inproceedings{sonowal-sadhu-2025-structure,
    title = "Structure-Aware Chunking for Abstractive Summarization of Long Legal Documents",
    author = "Sonowal, Himadri  and
      Sadhu, Saisab",
    editor = "Modi, Ashutosh  and
      Ghosh, Saptarshi  and
      Ekbal, Asif  and
      Goyal, Pawan  and
      Jain, Sarika  and
      Joshi, Abhinav  and
      Mishra, Shivani  and
      Datta, Debtanu  and
      Paul, Shounak  and
      Singh, Kshetrimayum Boynao  and
      Kumar, Sandeep",
    booktitle = "Proceedings of the 1st Workshop on NLP for Empowering Justice (JUST-NLP 2025)",
    month = dec,
    year = "2025",
    address = "Mumbai, India",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.justnlp-main.19/",
    pages = "171--178",
    ISBN = "979-8-89176-312-8",
    abstract = "The efficacy of state-of-the-art abstractive summarization models is severely constrained by the extreme document lengths of legal judgments, which consistently surpass their fixed input capacities. The prevailing method, naive sequential chunking, is a discourse-agnostic process that induces context fragmentation and degrades summary coherence. This paper introduces Structure-Aware Chunking (SAC), a rhetorically-informed pre-processing pipeline that leverages the intrinsic logical structure of legal documents. We partition judgments into their constituent rhetorical strata{---}Facts, Arguments {\&} Analysis, and Conclusion{---}prior to the summarization pass. We present and evaluate two SAC instantiations: a computationally efficient heuristic-based segmenter and a semantically robust LLM-driven approach. Empirical validation on the JUST-NLP 2025 L-SUMM shared task dataset reveals a nuanced trade-off: while our methods improve local, n-gram based metrics (ROUGE-2), they struggle to maintain global coherence (ROUGE-L). We identify this ``coherence gap'' as a critical challenge in chunk-based summarization and show that advanced LLM-based segmentation begins to bridge it."
}